Optional BLAST (remote). Comment out if you do not want network calls.
A comprehensive toolbox for computational molecular biology; use it when you need programmatic sequence/structure parsing, batch bioinformatics pipelines, or automated NCBI/BLAST workflows.
BY aipochUPDATED Oct 30, 2026
INTENDED FOR✳Claude Code>_Codex◈OpenClaw↗CursorInstall in a listed agent.
instructions.md
---
name: biopython-6312a7353bb7
description: A comprehensive toolbox for computational molecular biology; use it when you need programmatic sequence/structure parsing, batch bioinformatics pipelines, or automated NCBI/BLAST workflows.
license: MIT
author: AIPOCH
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
## When to Use
Use this skill when you need to:
- Batch-process DNA/RNA/protein sequences (translation, reverse complement, statistics) as part of a custom pipeline.
- Parse, validate, convert, or stream large bioinformatics files (FASTA/FASTQ/GenBank/PDB/mmCIF) without loading everything into memory.
- Programmatically query and download records from NCBI (GenBank, PubMed, Gene, Protein) via `Bio.Entrez`, respecting rate limits.
- Automate BLAST searches (web or local) and parse results to extract top hits and metadata.
- Build or manipulate phylogenetic trees from alignments or distance matrices (e.g., NJ trees) for downstream analysis.
> Note: For quick one-off queries, tools like **gget** may be more convenient; for multi-service API aggregation, **bioservices** may be a better fit.
## Key Features
- **Sequence objects and utilities**: `Bio.Seq`, `Bio.SeqRecord`, `Bio.SeqUtils` (GC fraction, molecular weight, translation, etc.).
- **File I/O and format conversion**: `Bio.SeqIO`, `Bio.AlignIO` for FASTA/FASTQ/GenBank and alignment formats.
- **NCBI access**: `Bio.Entrez` for `esearch`, `efetch`, `elink`, and structured parsing via `Entrez.read`.
- **BLAST**: `Bio.Blast.NCBIWWW` for remote BLAST and `Bio.Blast.NCBIXML` for XML parsing.
- **Structural bioinformatics**: `Bio.PDB` for PDB/mmCIF parsing, hierarchy traversal, and geometry calculations.
- **Phylogenetics**: `Bio.Phylo` and `Bio.Phylo.TreeConstruction` for tree I/O, distances, and construction.
Reference guides (if present in this repository) can be consulted for deeper module-specific patterns:
- `references/sequence_io.md`
- `references/alignment.md`
- `references/databases.md`
- `references/blast.md`
- `references/structure.md`
- `references/phylogenetics.md`
- `references/advanced.md`
## Dependencies
- Python **>= 3.8** (Biopython 1.85 supports Python 3)
- `biopython==1.85`
- `numpy>=1.20` (required by Biopython)
Install:
```bash
python -m pip install "biopython==1.85" "numpy>=1.20"
```
## Example Usage
A complete, runnable example that:
1) parses a FASTA file,
2) computes GC fraction,
3) runs a remote BLAST (optional),
4) fetches the top hit from NCBI,
5) prints basic results.
Create `example_biopython_pipeline.py`:
```python
from __future__ import annotations
import os
import time
from typing import Optional
from Bio import Entrez, SeqIO
from Bio.SeqUtils import gc_fraction
# Optional BLAST (remote). Comment out if you do not want network calls.
from Bio.Blast import NCBIWWW, NCBIXML
def configure_entrez() -> None:
"""
NCBI requires an email. An API key increases rate limits.
Set these via environment variables to avoid hardcoding secrets.
"""
email = os.environ.get("NCBI_EMAIL")
if not email:
raise RuntimeError("Set NCBI_EMAIL env var (required by NCBI). Example: export NCBI_EMAIL='you@org.org'")
Entrez.email = email
api_key = os.environ.get("NCBI_API_KEY")
if api_key:
Entrez.api_key = api_key
def read_first_fasta_record(path: str):
with open(path, "r", encoding="utf-8") as handle:
return next(SeqIO.parse(handle, "fasta"))
def blast_top_accession(sequence: str, program: str = "blastn", database: str = "nt") -> Optional[str]:
"""
Remote BLAST can be slow and rate-limited. For large-scale BLAST, prefer local BLAST+.
"""
result_handle = NCBIWWW.qblast(program, database, sequence)
blast_record = NCBIXML.read(result_handle)
if not blast_record.alignments:
return None
# Many BLAST titles include multiple identifiers; accession is usually available directly.
return blast_record.alignments[0].accession
def fetch_fasta_by_accession(accession: str) -> str:
with Entrez.efetch(db="nucleotide", id=accession, rettype="fasta", retmode="text") as handle:
return handle.read()
def main() -> None:
configure_entrez()
record = read_first_fasta_record("input.fasta")
seq = record.seq
print(f"ID: {record.id}")
print(f"Length: {len(seq)}")
print(f"GC fraction: {gc_fraction(seq):.2%}")
# Be polite to NCBI services in batch workflows.
time.sleep(0.34)
top_acc = blast_top_accession(str(seq))
if not top_acc:
print("No BLAST hits found.")
return
print(f"Top BLAST accession: {top_acc}")
time.sleep(0.34)
fasta_text = fetch_fasta_by_accession(top_acc)
print("Top hit FASTA:")
print(fasta_text)
if __name__ == "__main__":
main()
```
Run:
```bash
export NCBI_EMAIL="your.email@example.com"
# export NCBI_API_KEY="your_ncbi_api_key" # optional
python example_biopython_pipeline.py
```
Provide an `input.fasta` in the same directory, e.g.:
```text
>demo
ATCGATCGATCGATCGATCG
```
## Implementation Details
- **Streaming I/O for large datasets**: Prefer iterator-based parsing (`SeqIO.parse`) to avoid loading entire files into memory. Use `SeqIO.read` only when exactly one record is expected.
- **Entrez configuration and rate limits**:
- Always set `Entrez.email` (NCBI requirement).
- Optionally set `Entrez.api_key` to increase request limits.
- In batch jobs, add delays (e.g., `time.sleep(0.34)` as a conservative baseline) and implement retries for transient HTTP failures.
- **BLAST considerations**:
- `NCBIWWW.qblast(...)` is convenient but can be slow and is not ideal for high-throughput workloads.
- Parse results with `NCBIXML.read(...)` (single record) or `NCBIXML.parse(...)` (multiple records).
- Filter hits by HSP metrics (e-value, identity) by iterating `alignment.hsps`.
- **Sequence statistics and transformations**:
- Use `Bio.SeqUtils.gc_fraction(seq)` for GC fraction (returns 0–1).
- Use `seq.translate(table=...)` with the correct genetic code table for reproducibility.
- **Structure parsing (if used)**:
- Use `Bio.PDB.PDBParser(QUIET=True)` to suppress warnings when appropriate.
- Navigate the SMCRA hierarchy (Structure → Model → Chain → Residue → Atom) for robust traversal and geometry calculations.
- **Reproducibility**:
- Record key parameters (file formats, translation table, BLAST program/database, e-value thresholds, NCBI query terms).
- Cache downloaded records when iterating to avoid repeated network calls.
---
name: biopython-6312a7353bb7
description: A comprehensive toolbox for computational molecular biology; use it when you need programmatic sequence/structure parsing, batch bioinformatics pipelines, or automated NCBI/BLAST workflows.
license: MIT
author: AIPOCH
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
## When to Use
Use this skill when you need to:
- Batch-process DNA/RNA/protein sequences (translation, reverse complement, statistics) as part of a custom pipeline.
- Parse, validate, convert, or stream large bioinformatics files (FASTA/FASTQ/GenBank/PDB/mmCIF) without loading everything into memory.
- Programmatically query and download records from NCBI (GenBank, PubMed, Gene, Protein) via `Bio.Entrez`, respecting rate limits.
- Automate BLAST searches (web or local) and parse results to extract top hits and metadata.
- Build or manipulate phylogenetic trees from alignments or distance matrices (e.g., NJ trees) for downstream analysis.
> Note: For quick one-off queries, tools like **gget** may be more convenient; for multi-service API aggregation, **bioservices** may be a better fit.
## Key Features
- **Sequence objects and utilities**: `Bio.Seq`, `Bio.SeqRecord`, `Bio.SeqUtils` (GC fraction, molecular weight, translation, etc.).
- **File I/O and format conversion**: `Bio.SeqIO`, `Bio.AlignIO` for FASTA/FASTQ/GenBank and alignment formats.
- **NCBI access**: `Bio.Entrez` for `esearch`, `efetch`, `elink`, and structured parsing via `Entrez.read`.
- **BLAST**: `Bio.Blast.NCBIWWW` for remote BLAST and `Bio.Blast.NCBIXML` for XML parsing.
- **Structural bioinformatics**: `Bio.PDB` for PDB/mmCIF parsing, hierarchy traversal, and geometry calculations.
- **Phylogenetics**: `Bio.Phylo` and `Bio.Phylo.TreeConstruction` for tree I/O, distances, and construction.
Reference guides (if present in this repository) can be consulted for deeper module-specific patterns:
- `references/sequence_io.md`
- `references/alignment.md`
- `references/databases.md`
- `references/blast.md`
- `references/structure.md`
- `references/phylogenetics.md`
- `references/advanced.md`
## Dependencies
- Python **>= 3.8** (Biopython 1.85 supports Python 3)
- `biopython==1.85`
- `numpy>=1.20` (required by Biopython)
Install:
```bash
python -m pip install "biopython==1.85" "numpy>=1.20"
```
## Example Usage
A complete, runnable example that:
1) parses a FASTA file,
2) computes GC fraction,
3) runs a remote BLAST (optional),
4) fetches the top hit from NCBI,
5) prints basic results.
Create `example_biopython_pipeline.py`:
```python
from __future__ import annotations
import os
import time
from typing import Optional
from Bio import Entrez, SeqIO
from Bio.SeqUtils import gc_fraction
# Optional BLAST (remote). Comment out if you do not want network calls.
from Bio.Blast import NCBIWWW, NCBIXML
def configure_entrez() -> None:
"""
NCBI requires an email. An API key increases rate limits.
Set these via environment variables to avoid hardcoding secrets.
"""
email = os.environ.get("NCBI_EMAIL")
if not email:
raise RuntimeError("Set NCBI_EMAIL env var (required by NCBI). Example: export NCBI_EMAIL='you@org.org'")
Entrez.email = email
api_key = os.environ.get("NCBI_API_KEY")
if api_key:
Entrez.api_key = api_key
def read_first_fasta_record(path: str):
with open(path, "r", encoding="utf-8") as handle:
return next(SeqIO.parse(handle, "fasta"))
def blast_top_accession(sequence: str, program: str = "blastn", database: str = "nt") -> Optional[str]:
"""
Remote BLAST can be slow and rate-limited. For large-scale BLAST, prefer local BLAST+.
"""
result_handle = NCBIWWW.qblast(program, database, sequence)
blast_record = NCBIXML.read(result_handle)
if not blast_record.alignments:
return None
# Many BLAST titles include multiple identifiers; accession is usually available directly.
return blast_record.alignments[0].accession
def fetch_fasta_by_accession(accession: str) -> str:
with Entrez.efetch(db="nucleotide", id=accession, rettype="fasta", retmode="text") as handle:
return handle.read()
def main() -> None:
configure_entrez()
record = read_first_fasta_record("input.fasta")
seq = record.seq
print(f"ID: {record.id}")
print(f"Length: {len(seq)}")
print(f"GC fraction: {gc_fraction(seq):.2%}")
# Be polite to NCBI services in batch workflows.
time.sleep(0.34)
top_acc = blast_top_accession(str(seq))
if not top_acc:
print("No BLAST hits found.")
return
print(f"Top BLAST accession: {top_acc}")
time.sleep(0.34)
fasta_text = fetch_fasta_by_accession(top_acc)
print("Top hit FASTA:")
print(fasta_text)
if __name__ == "__main__":
main()
```
Run:
```bash
export NCBI_EMAIL="your.email@example.com"
# export NCBI_API_KEY="your_ncbi_api_key" # optional
python example_biopython_pipeline.py
```
Provide an `input.fasta` in the same directory, e.g.:
```text
>demo
ATCGATCGATCGATCGATCG
```
## Implementation Details
- **Streaming I/O for large datasets**: Prefer iterator-based parsing (`SeqIO.parse`) to avoid loading entire files into memory. Use `SeqIO.read` only when exactly one record is expected.
- **Entrez configuration and rate limits**:
- Always set `Entrez.email` (NCBI requirement).
- Optionally set `Entrez.api_key` to increase request limits.
- In batch jobs, add delays (e.g., `time.sleep(0.34)` as a conservative baseline) and implement retries for transient HTTP failures.
- **BLAST considerations**:
- `NCBIWWW.qblast(...)` is convenient but can be slow and is not ideal for high-throughput workloads.
- Parse results with `NCBIXML.read(...)` (single record) or `NCBIXML.parse(...)` (multiple records).
- Filter hits by HSP metrics (e-value, identity) by iterating `alignment.hsps`.
- **Sequence statistics and transformations**:
- Use `Bio.SeqUtils.gc_fraction(seq)` for GC fraction (returns 0–1).
- Use `seq.translate(table=...)` with the correct genetic code table for reproducibility.
- **Structure parsing (if used)**:
- Use `Bio.PDB.PDBParser(QUIET=True)` to suppress warnings when appropriate.
- Navigate the SMCRA hierarchy (Structure → Model → Chain → Residue → Atom) for robust traversal and geometry calculations.
- **Reproducibility**:
- Record key parameters (file formats, translation table, BLAST program/database, e-value thresholds, NCBI query terms).
- Cache downloaded records when iterating to avoid repeated network calls.
COMPATIBILITY & REFERENCES
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.
---name: liquid-biopsy-analytics-agent description: AI-powered comprehensive liquid biopsy analysis integrating ctDNA, CTCs, exosomes, and cfRNA for cancer detection, monitoring, and treatment guidance. license: MIT metadata: author: AI Group version: "1.0.0" created: "2026-01-19" compatibility:
Remove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables. Use when correcting batch effects in expression data.
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies ...
Generate reproducible bioinformatics/data-science Methods + run documentation from workflow run artifacts (Nextflow/Snakemake/CWL), including a top-of-doc workflow summary, exact executed commands, tool versions, parameters, QC, and outputs.